The main purpose of this research is to run computer simulations to evaluate a new method of handling missing data. The method proposed by the present investigator replaces the missing information by a "best" estimate based on the available information in the data set plus a random component. This new method is different from other methods in that a random component is added to the "best" estimate of the missing information. Preliminary studies indicate that this new method is generally superior to other methods of replacing missing data, such as substituting (for missing information) overall means or regression estimates, or estimates based on principal component analysis, when relatively large numbers of variables are under consideration and data are randomly missing. Still at issue is this method's relative efficiency under a variety of different research conditions--size of the sample, the relative proportion and different configuration of missing data, the degree of association among the variables, and so on. A computer simulation is ideal for resolving such an issue. The results of the research should establish conditions under which the proposed method can be safely used.